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Exploring of alternative representations of facial images for face recognition

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Abstract

Description and classification of face images is a significant task of computer vision, machine learning and pattern recognition communities. In the past, researchers have made tremendous efforts in this task. Previous researchers always seek high-resolution face images for better image classification. However, with this paper, we present and demonstrate a new opinion that in some cases the use of alternative representations of facial images are very useful for face recognition and properly reducing the image resolution might be beneficial to better classification of face images. This may be attributed to the deformable property of faces and the fact that the proposed alternative representations can in some extent reduce the within-class difference of facial images. Also, the presented idea appear to be useful for helping people to improve face recognition techniques in real worlds.

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Acknowledgements

This work is supported by Major Research Program of the National Natural Science Foundation of China under Grant No.91746116, the Major Applied Basic Research Program of Guizhou Province under Grant No. JZ20142001 and the Major Special Science and Technology Projects of Guizhou Province under Grant No. [2017]3002.

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Authors and Affiliations

  1. Guizhou Provincial Key Laboratory of Public Big Data, Guizhou University, North Section of Huaxi Road, 550025, Guiyang, China

    Yongbin Qin, Lilei Sun & Yong Xu

  2. College of Computer Science and Technology, Guizhou University, North Section of Huaxi Road, 550025, Guiyang, China

    Yongbin Qin, Lilei Sun & Yong Xu

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  1. Yongbin Qin
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  2. Lilei Sun
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  3. Yong Xu
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Correspondence to Yong Xu.

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Qin, Y., Sun, L. & Xu, Y. Exploring of alternative representations of facial images for face recognition. Int. J. Mach. Learn. & Cyber. 11, 2289–2295 (2020). https://doi.org/10.1007/s13042-020-01116-4

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  • DOI: https://doi.org/10.1007/s13042-020-01116-4

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